code: def test_is_pd(self):
      # ensures 1d input is positive definite with additional jitter
      x = torch.randn(100).reshape(-1, 1)
      kernel = PeriodicKernel()
      with torch.no_grad():
          K = kernel(x, x).to_dense() + 1e-4 * torch.eye(len(x))
          eig = torch.linalg.eigvalsh(K)
          self.assertTrue((eig > 0.0).all().item())
  
file_path: gpytorch/test/kernels/test_periodic_kernel.py
imports: import math
  import unittest
  import torch
  from gpytorch.kernels import PeriodicKernel
  from gpytorch.priors import NormalPrior
  from gpytorch.test.base_kernel_test_case import BaseKernelTestCase
label_desc: Use image node_id 4 for calling the TestPeriodicKernel obj's underlying member method code with example usage: obj.test_is_pd() without return types